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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1994 Working Papers
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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1994 Working Papers
      • View Item
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      WEKA: a machine learning workbench

      Holmes, Geoffrey; Donkin, Andrew; Witten, Ian H.
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      Holmes, G., Donkin, A. & Witten, I.H. (1994). WEKA: a machine learning workbench. (Working paper 94/09). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
      Permanent Research Commons link: https://hdl.handle.net/10289/1138
      Abstract
      Weka is a workbench for machine learning that is intended to aid in the application of machine learning techniques to a variety of real-world problems, in particular, those arising from agricultural and horticultural domains. Unlike other machine learning projects, the emphasis is on providing a working environment for the domain specialist rather than the machine learning expert. Lessons learned include the necessity of providing a wealth of interactive tools for data manipulation, result visualization, database linkage, and cross-validation and comparison of rule sets, to complement the basic machine learning tools.
      Date
      1994-07
      Type
      Working Paper
      Series
      Computer Science Working Papers
      Report No.
      94/09
      Collections
      • 1994 Working Papers [18]
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